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An integration analysis based on genomic, transcriptomic and QTX information reveals credible candidate genes for fat‐related traits in pigs
Author(s) -
Fu Y.,
Wang L.,
Tang Z.,
Yin D.,
Xu J.,
Fan Y.,
Li X.,
Zhao S.,
Liu X.
Publication year - 2020
Publication title -
animal genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.756
H-Index - 81
eISSN - 1365-2052
pISSN - 0268-9146
DOI - 10.1111/age.12971
Subject(s) - candidate gene , biology , genetics , gene , transcriptome , genome , identification (biology) , quantitative trait locus , computational biology , genomics , gene expression , botany
Summary Meat quality improvement is of great interest to researchers in pig breeding and many researchers have identified abundant associated quantitative trait loci, genes and polymorphisms (QTXs) for fat‐related traits. However, it is challenging to determine credible candidate genes from a mass of associations. The efficiency of identification of credible candidate genes in these QTXs is restricted by limited integration analyses of data from multiple omics. In this study, we constructed a ‘candidate gene map’ of fat‐related traits in pigs based on published literature and the latest genome. In total, 6,861 QTXs, which covered 9,323 genes on the pig genome, were used. Combining the QTX hotspots and pathway analysis, we identified 180 candidate genes that may regulate the fat‐related traits, and choose PNPLA2 , PPARG , SREBF1 , ACACA , PPARD and PPARA as credible candidate genes. In addition, we discussed the importance of incorporating transcriptome data and genomic data in causal gene identification, and the multi‐omics information can effectively improve the credibility of identified candidate genes.